head JofIMAB
Journal of IMAB - Annual Proceeding (Scientific Papers)
Publisher: Peytchinski Publishing
ISSN: 1312-773X (Online)
Issue: 2017, vol. 23, issue 4
Subject Area: Dental Medicine
DOI: 10.5272/jimab.2017234.1784
Published online: 05 December 2017

Original article

J of IMAB 2017 Oct-Dec;23(4):1784-1789
Stefan ZlatevORCID logo Corresponding Autoremail, Hristo KissovORCID logo, Viktor HadzhigaevORCID logo, Ilian HristovORCID logo,
Department of Prosthetic Dentistry, Faculty of Dental Medicine, Medical University Plovdiv, Bulgaria.

Introduction: A drastic increase in the number of published medical papers per year is observed. This makes the identification, analysis and categorization of significant studies a difficult task. Natural (human) Language Processing and text mining are methods, part of the scientific branch computer linguistics that transfer the informational overload from a human to a computer. It enables easier processing and analysis of large volumes of unstructured textual data.
Purpose: The current study aims to familiarize researchers working in the field of dentistry with the capabilities of NLP and TM for a quick and concise analysis of large volumes of unstructured textual information and identification of dependencies between different factors important for a given subject.
Materials and Methods: To demonstrate the capabilities of text mining, an important topic in the field of dentistry was chosen – factors influencing the esthetics of a smile. The analysis was carried out with “R”- a computer language for statistical processing. A literature search was conducted in the “PubMed” database with key-words – “dental, esthetic and factor”. The resulting abstracts were saved as a local copy, imported and processed. Word frequencies and associations between different terms were analyzed.
Results and discussion: Weak to moderate correlation was established between the significant, most frequent terms in the text - “esthetics, „smile“, „arc“, „buccal“, „gingival”, “lip” and “midline”./0.1<r<0.45/ Word combinations and frequencies resulting from the analysis are in agreement with other reported findings.
Conclusion: NLP and text mining are valuable tools which decrease the time necessary for analysis of large volumes of data. The results can aid further research with increased accuracy. .

Keywords: text mining, natural language processing, smile, factors, esthetics,

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Please cite this article in PubMed Style or AMA (American Medical Association) Style:
Zlatev S, Kissov H, Hadzhigaev V, Hristov I. Natural language processing as a method for evaluation of factors influencing smile attractiveness. J of IMAB. 2017 Oct-Dec;23(4):1784-1789. DOI: 10.5272/jimab.2017234.1784

Corresponding AutorCorrespondence to: Stefan Chavdarov Zlatev, Department of Prosthetic Dentistry, Faculty of Dental Medicine, Medical University - Plovdiv; 3, Hristo Botev str., 4000 Plovdiv, Bulgaria; E-mail: stefanzlatevdr@gmail.com

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Received: 21 June 2017
Published online: 05 December 2017

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